Artificial intelligence in marketing: A meta‐analytic review. Issue 11 (8th August 2022)

• Record Type: Journal Article
• Authors: Mehta, Pooja; Jebarajakirthy, Charles; Maseeh, Haroon Iqbal; Anubha, Anubha; Saha, Raiswa; Dhanda, Komal
• Is Part Of: Psychology & marketing. Volume 39:Issue 11(2022)
• Page Start: 2013
• Page End: 2038
• Publication Date: 2022-08-08
• Subjects: artificial intelligence -- meta‐analysis -- theory of reasoned action -- unified theory of acceptance and use of technology 2; Marketing -- Psychological aspects -- Periodicals; Motivation research (Marketing) -- Periodicals; Marketing -- Aspect psychologique -- Périodiques; Motivation, Études de (Marketing) -- Périodiques; 658.80019
• DOI: 10.1002/mar.21716
• Languages: English
• ISSNs: 0742-6046

Abstract

Abstract: This study synthesizes the artificial intelligence literature into a Meta‐analytic framework based on the theory of reasoned action and the unified theory of acceptance and use of technology 2, and examines concrete relationships between the constructs of this framework. This meta‐review also performed a moderation analysis to investigate the possible reasons for inconsistent findings across studies. The findings suggest that three methodological moderators (sample type, gender dominance, and publication type), and one contextual moderator (level of country's technology advancement) lead to inconsistencies in the relationships between study constructs. Academically, this review synthesizes the artificial intelligence literature and resolves inconsistencies in the literature and also adds constructs to both theory of reasoned action and the unified theory of acceptance and use of technology 2. Practically, this meta‐analysis offers multiple implications for businesses interested in enhancing customer adoption of artificial intelligence. Especially, companies can increase customers' adoption of artificial intelligence by making it more user‐friendly, and advantageous and by adding pleasing features to it.